This document presents maps of Baltimore City integrating two sources of data: intake data from BARCS layered on top of Baltimore’s demographic data. This allows us to connect geographical patterns identified in the shelter data to the characteristics of the community.
The demographic data shown in the following maps is sourced from the U.S. Census using the 2022 five-year American Community Survey (ACS). Data is shown only for Census Tracts within Baltimore City, as this is BARCS’s jurisdiction. The demographic data can be toggled in the upper part of the map control panel, and it includes:
Layers 1-4: race/ethnicity data (% of each census tract identifying as the given race).
Layers 5-8: data regarding income and housing.Below Poverty 100% refers to the % of residents that are below the federal poverty line, and Owner Occupied is similarly represented as a percent value of residents.
Layers 9-11: language data, using the percentage of residents speaking only the given language and not English. Layer 12 enables a view without any Census data.
Additionally, intake data can be layered on top of the demographic data, controlled through the lower half of the map control panel. Data for 2022-2023 is visualized, showing 25621 intakes (including Service In). Only animals with sufficient location data (normally a specific address or an intersection) are visualized. The bottom section of the document shows the availability of location data by intake type. There are different layers for each intake type, in addition to the first layer containing all intakes. The size of the circle corresponds to the number of intakes from that location and you can click on circles to see how many intakes they represent.
The next sections have more maps showing other aspects of BARCS/Baltimore data. The first shows the locations of owner surrenders and returns by intake reason. Other tabs show maps with the existing KPWF data, the different Service In intakes, and microchip status on intake.
General Use Note: if at any point one of the maps freezes, smears, or becomes messy in some other way, just refresh the whole page and let it fully reload.
This map visualizes OS and Returns intakes by intake reason. 2491 animals that have one of the four intake reasons groups indicated in the legend (housing, cost, behavior, medical) are shown out of 5432 owner surrenders and returns in total present in the data. Animals without reasons (1913), with general reasons, and with reasons related to owner/household preferences or life circumstances were not visualized (the latter because they are less clearly linked to a potential service or intervention).
Icon size is larger in places with more than one surrender. There are at most 10 surrenders per icon, with three icon sizes used to differentiate between them (1, 2-5, 6+). You can click an icon to see ow many housing-related OS it represents (same goes for clicking any intake circles).
This map visualizes some of the existing KPWF shared with us that could be mapped - S/N recipients and Pop-Up locations. After we review the data currently being tracking we can revise this as needed.
This maps shows the separate Service In intakes by subtype to allow us to see the locations of recipients of different services separately.
This maps explore microchips at intake, with separate layers showing the found locations of animals found with, without, or with unknown microchip status (green, red, and grey, respectively). Only stray intakes are visualized.
The following table summarizes the quality of geographical data available in the data for each intake type. “No Address” means there was no address or that the address listed was the shelter’s address (any variation of 2490 Giles Rd). “Incomplete address” means there was an address, but it was not accurate enough to be mapped, for example using a street name without a number. Only “Complete” addresses were geocoded, and the success rate of the geocoding is shown. The final column shows what percentage of that intake category is represented in the maps.
Insight: All intake types except Strays had excellent data completeness. Only 72% of all strays ended up being visualized, which is a bit lower than we would hope (a good rule of thumb is 80%). Common ways addresses were incomplete included indicating street-name only (without a number) and a relative rather than absolute location (e.g. behind the house, next to the late). One good example of data entry in incomplete cases was mentioning a block number (e.g. 1000 X street, or 1000 blk of Y street). This allows an accurate-enough mapping even when the precise location was not available.
| Intake Type | Total | No Address | Incomplete Address | Complete Address | Complete Addr. % | Geocoded | Geocoding Success % | % of Total Geocoded |
|---|---|---|---|---|---|---|---|---|
| OS | 4731 | 52 | 50 | 4629 | 98% | 4375 | 95% | 92% |
| ORE | 680 | 6 | 7 | 667 | 98% | 644 | 97% | 95% |
| Return | 1058 | 4 | 24 | 1030 | 97% | 1000 | 97% | 95% |
| Seized | 3622 | 15 | 75 | 3532 | 98% | 3322 | 94% | 92% |
| Service In | 8225 | 151 | 172 | 7902 | 96% | 7752 | 98% | 94% |
| Stray | 9036 | 241 | 1647 | 7148 | 79% | 6492 | 91% | 72% |